HackUCI Data Science Hack Winner (Monopoly Simulation)

These are the most landed upon spaces in Monopoly. Jail is the most popular and spaces a dice roll after are popular spaces.

This shows the best short-term investments on breaking even on single property investments. In early game, Utilities and Railroads are good.

This graph shows the best long term investments. It shows how quickly a number of houses will break even.

Inspiration

Interested in running game simulations and porting it over to real life simulations, we decided on compiling statistics for the complex game of Monopoly.

What it does

We had two methods of finding the best strategies:
1) Simulate a character moving around the board many times and compile statistics for the most popular spaces
2) Create an AI that values different properties and strategies to find the best strategies

How I built it

In order to be accurate to the game and percentages, we wrote a program to simulate every rule of Monopoly. These rules include Community Chest, Chance, three double rolls lead to jail, staying in jail, dice rolls, and property rents.
We then simulated a character rolling dice many times to keep track of all the popular places. Finally, we compiled statistics on what value each property had.

Challenges I ran into

Making the game itself had many intricate rules that involved many exceptions that we had to account for. Some of the math behind the statistics we had to discover on the way.

Accomplishments that I'm proud of

The graphs visualize the best strategies well and are aesthetically pleasing. We were able to glean quite a bit from the numbers we found.

What I learned

From the statistics that gained, Jail is such a popular place to land that spaces a dice roll away from Jail are the most optimal spots to buy property. We analyzed both short-term and long-term investments and concluded that in short term, buying Utilities and Railroads are good investments. In the long-term, buying single properties is not as optimal as upgrading to the third house after buying a set of houses.

On a meta level, we gained experience on simulations that we can apply elsewhere like simulating nature, sports, and other events. We learned about data visualizations and interpreting this data.

What's next for Monopoly Simulation

We can optimize an AI for playing Monopoly that actually takes different strategies into account. It will value different properties differently so we can find the best properties and strategies.